In multi-sensor tracking systems a process of associating sets of observations from at least two sensor systems is problematic in the presence of bias, random errors, false observations, and missed observations. For example, one tracking system may share data with the other system and transmit its current set of its observations to the other sensor system. The second sensor system determines which data points received from the first sensor system correspond to the airplanes it is also tracking. In practice, the process is difficult because each sensor system has an associated error, making it problematic to assign a data point from one sensor system to the other sensor system. Examples of errors may include misalignment between the two sensor systems, different levels of tolerances, and/or one sensor system may observe certain types of airplanes while the other sensor system does not observe the same types of aircraft. Therefore, based on each particular sensor system having errors due to bias, random errors, false observations, and missed observations, it is difficult to use a set of data received from the first sensor system and directly overlay it with a set of data from the second sensor system.